LibreChat/api/app/clients/prompts/formatMessages.js
Danny Avila a0291ed155
🚧 chore: merge latest dev build to main repo (#3844)
* agents - phase 1 (#30)

* chore: copy assistant files

* feat: frontend and data-provider

* feat: backend get endpoint test

* fix(MessageEndpointIcon): switched to AgentName and AgentAvatar

* fix: small fixes

* fix: agent endpoint config

* fix: show Agent Builder

* chore: install agentus

* chore: initial scaffolding for agents

* fix: updated Assistant logic to Agent Logic for some Agent components

* WIP first pass, demo of agent package

* WIP: initial backend infra for agents

* fix: agent list error

* wip: agents routing

* chore: Refactor useSSE hook to handle different data events

* wip: correctly emit events

* chore: Update @librechat/agentus npm dependency to version 1.0.9

* remove comment

* first pass: streaming agent text

* chore: Remove @librechat/agentus root-level workspace npm dependency

* feat: Agent Schema and Model

* fix: content handling fixes

* fix: content message save

* WIP: new content data

* fix: run step issue with tool calls

* chore: Update @librechat/agentus npm dependency to version 1.1.5

* feat: update controller and agent routes

* wip: initial backend tool and tool error handling support

* wip: tool chunks

* chore: Update @librechat/agentus npm dependency to version 1.1.7

* chore: update tool_call typing, add test conditions and logs

* fix: create agent

* fix: create agent

* first pass: render completed content parts

* fix: remove logging, fix step handler typing

* chore: Update @librechat/agentus npm dependency to version 1.1.9

* refactor: cleanup maps on unmount

* chore: Update BaseClient.js to safely count tokens for string, number, and boolean values

* fix: support subsequent messages with tool_calls

* chore: export order

* fix: select agent

* fix: tool call types and handling

* chore: switch to anthropic for testing

* fix: AgentSelect

* refactor: experimental: OpenAIClient to use array for intermediateReply

* fix(useSSE): revert old condition for streaming legacy client tokens

* fix: lint

* revert `agent_id` to `id`

* chore: update localization keys for agent-related components

* feat: zod schema handling for actions

* refactor(actions): if no params, no zodSchema

* chore: Update @librechat/agentus npm dependency to version 1.2.1

* feat: first pass, actions

* refactor: empty schema for actions without params

* feat: Update createRun function to accept additional options

* fix: message payload formatting; feat: add more client options

* fix: ToolCall component rendering when action has no args but has output

* refactor(ToolCall): allow non-stringy args

* WIP: first pass, correctly formatted tool_calls between providers

* refactor: Remove duplicate import of 'roles' module

* refactor: Exclude 'vite.config.ts' from TypeScript compilation

* refactor: fix agent related types
> - no need to use endpoint/model fields for identifying agent metadata
> - add `provider` distinction for agent-configured 'endpoint'
- no need for agent-endpoint map
- reduce complexity of tools as functions into tools as string[]
- fix types related to above changes
- reduce unnecessary variables for queries/mutations and corresponding react-query keys

* refactor: Add tools and tool_kwargs fields to agent schema

* refactor: Remove unused code and update dependencies

* refactor: Update updateAgentHandler to use req.body directly

* refactor: Update AgentSelect component to use localized hooks

* refactor: Update agent schema to include tools and provider fields

* refactor(AgentPanel): add scrollbar gutter, add provider field to form, fix agent schema required values

* refactor: Update AgentSwitcher component to use selectedAgentId instead of selectedAgent

* refactor: Update AgentPanel component to include alternateName import and defaultAgentFormValues

* refactor(SelectDropDown): allow setting value as option while still supporting legacy usage (string values only)

* refactor: SelectDropdown changes - Only necessary when the available values are objects with label/value fields and the selected value is expected to be a string.

* refactor: TypeError issues and handle provider as option

* feat: Add placeholder for provider selection in AgentPanel component

* refactor: Update agent schema to include author and provider fields

* fix: show expected 'create agent' placeholder when creating agent

* chore: fix localization strings, hide capabilities form for now

* chore: typing

* refactor: import order and use compact agents schema for now

* chore: typing

* refactor: Update AgentForm type to use AgentCapabilities

* fix agent form agent selection issues

* feat: responsive agent selection

* fix: Handle cancelled fetch in useSelectAgent hook

* fix: reset agent form on accordion close/open

* feat: Add agent_id to default conversation for agents endpoint

* feat: agents endpoint request handling

* refactor: reset conversation model on agent select

* refactor: add `additional_instructions` to conversation schema, organize other fields

* chore: casing

* chore: types

* refactor(loadAgentTools): explicitly pass agent_id, do not pass `model` to loadAgentTools for now, load action sets by agent_id

* WIP: initial draft of real agent client initialization

* WIP: first pass, anthropic agent requests

* feat: remember last selected agent

* feat: openai and azure connected

* fix: prioritize agent model for runs unless an explicit override model is passed from client

* feat: Agent Actions

* fix: save agent id to convo

* feat: model panel (#29)

* feat: model panel

* bring back comments

* fix: method still null

* fix: AgentPanel FormContext

* feat: add more parameters

* fix: style issues; refactor: Agent Controller

* fix: cherry-pick

* fix: Update AgentAvatar component to use AssistantIcon instead of BrainCircuit

* feat: OGDialog for delete agent; feat(assistant): update Agent types, introduced `model_parameters`

* feat: icon and general `model_parameters` update

* feat: use react-hook-form better

* fix: agent builder form reset issue when switching panels

* refactor: modularize agent builder form

---------

Co-authored-by: Danny Avila <danny@librechat.ai>

* fix: AgentPanel and ModelPanel type issues and use `useFormContext` and `watch` instead of `methods` directly and `useWatch`.

* fix: tool call issues due to invalid input (anthropic) of empty string

* fix: handle empty text in Part component

---------

Co-authored-by: Marco Beretta <81851188+berry-13@users.noreply.github.com>

* refactor: remove form ModelPanel and fixed nested ternary expressions in AgentConfig

* fix: Model Parameters not saved correctly

* refactor: remove console log

* feat: avatar upload and get for Agents (#36)

Co-authored-by: Marco Beretta <81851188+berry-13@users.noreply.github.com>

* chore: update to public package

* fix: typing, optional chaining

* fix: cursor not showing for content parts

* chore: conditionally enable agents

* ci: fix azure test

* ci: fix frontend tests, fix eslint api

* refactor: Remove unused errorContentPart variable

* continue of the agent message PR (#40)

* last fixes

* fix: agentMap

* pr merge test  (#41)

* fix: model icon not fetching correctly

* remove console logs

* feat: agent name

* refactor: pass documentsMap as a prop to allow re-render of assistant form

* refactor: pass documentsMap as a prop to allow re-render of assistant form

* chore: Bump version to 0.7.419

* fix: TypeError: Cannot read properties of undefined (reading 'id')

* refactor: update AgentSwitcher component to use ControlCombobox instead of Combobox

---------

Co-authored-by: Marco Beretta <81851188+berry-13@users.noreply.github.com>
2024-08-31 16:33:51 -04:00

202 lines
7.4 KiB
JavaScript

const { ToolMessage } = require('@langchain/core/messages');
const { EModelEndpoint, ContentTypes } = require('librechat-data-provider');
const { HumanMessage, AIMessage, SystemMessage } = require('langchain/schema');
/**
* Formats a message to OpenAI Vision API payload format.
*
* @param {Object} params - The parameters for formatting.
* @param {Object} params.message - The message object to format.
* @param {string} [params.message.role] - The role of the message sender (must be 'user').
* @param {string} [params.message.content] - The text content of the message.
* @param {EModelEndpoint} [params.endpoint] - Identifier for specific endpoint handling
* @param {Array<string>} [params.image_urls] - The image_urls to attach to the message.
* @returns {(Object)} - The formatted message.
*/
const formatVisionMessage = ({ message, image_urls, endpoint }) => {
if (endpoint === EModelEndpoint.anthropic) {
message.content = [...image_urls, { type: ContentTypes.TEXT, text: message.content }];
return message;
}
message.content = [{ type: ContentTypes.TEXT, text: message.content }, ...image_urls];
return message;
};
/**
* Formats a message to OpenAI payload format based on the provided options.
*
* @param {Object} params - The parameters for formatting.
* @param {Object} params.message - The message object to format.
* @param {string} [params.message.role] - The role of the message sender (e.g., 'user', 'assistant').
* @param {string} [params.message._name] - The name associated with the message.
* @param {string} [params.message.sender] - The sender of the message.
* @param {string} [params.message.text] - The text content of the message.
* @param {string} [params.message.content] - The content of the message.
* @param {Array<string>} [params.message.image_urls] - The image_urls attached to the message for Vision API.
* @param {string} [params.userName] - The name of the user.
* @param {string} [params.assistantName] - The name of the assistant.
* @param {string} [params.endpoint] - Identifier for specific endpoint handling
* @param {boolean} [params.langChain=false] - Whether to return a LangChain message object.
* @returns {(Object|HumanMessage|AIMessage|SystemMessage)} - The formatted message.
*/
const formatMessage = ({ message, userName, assistantName, endpoint, langChain = false }) => {
let { role: _role, _name, sender, text, content: _content, lc_id } = message;
if (lc_id && lc_id[2] && !langChain) {
const roleMapping = {
SystemMessage: 'system',
HumanMessage: 'user',
AIMessage: 'assistant',
};
_role = roleMapping[lc_id[2]];
}
const role = _role ?? (sender && sender?.toLowerCase() === 'user' ? 'user' : 'assistant');
const content = _content ?? text ?? '';
const formattedMessage = {
role,
content,
};
const { image_urls } = message;
if (Array.isArray(image_urls) && image_urls.length > 0 && role === 'user') {
return formatVisionMessage({
message: formattedMessage,
image_urls: message.image_urls,
endpoint,
});
}
if (_name) {
formattedMessage.name = _name;
}
if (userName && formattedMessage.role === 'user') {
formattedMessage.name = userName;
}
if (assistantName && formattedMessage.role === 'assistant') {
formattedMessage.name = assistantName;
}
if (formattedMessage.name) {
// Conform to API regex: ^[a-zA-Z0-9_-]{1,64}$
// https://community.openai.com/t/the-format-of-the-name-field-in-the-documentation-is-incorrect/175684/2
formattedMessage.name = formattedMessage.name.replace(/[^a-zA-Z0-9_-]/g, '_');
if (formattedMessage.name.length > 64) {
formattedMessage.name = formattedMessage.name.substring(0, 64);
}
}
if (!langChain) {
return formattedMessage;
}
if (role === 'user') {
return new HumanMessage(formattedMessage);
} else if (role === 'assistant') {
return new AIMessage(formattedMessage);
} else {
return new SystemMessage(formattedMessage);
}
};
/**
* Formats an array of messages for LangChain.
*
* @param {Array<Object>} messages - The array of messages to format.
* @param {Object} formatOptions - The options for formatting each message.
* @param {string} [formatOptions.userName] - The name of the user.
* @param {string} [formatOptions.assistantName] - The name of the assistant.
* @returns {Array<(HumanMessage|AIMessage|SystemMessage)>} - The array of formatted LangChain messages.
*/
const formatLangChainMessages = (messages, formatOptions) =>
messages.map((msg) => formatMessage({ ...formatOptions, message: msg, langChain: true }));
/**
* Formats a LangChain message object by merging properties from `lc_kwargs` or `kwargs` and `additional_kwargs`.
*
* @param {Object} message - The message object to format.
* @param {Object} [message.lc_kwargs] - Contains properties to be merged. Either this or `message.kwargs` should be provided.
* @param {Object} [message.kwargs] - Contains properties to be merged. Either this or `message.lc_kwargs` should be provided.
* @param {Object} [message.kwargs.additional_kwargs] - Additional properties to be merged.
*
* @returns {Object} The formatted LangChain message.
*/
const formatFromLangChain = (message) => {
const { additional_kwargs, ...message_kwargs } = message.lc_kwargs ?? message.kwargs;
return {
...message_kwargs,
...additional_kwargs,
};
};
/**
* Formats an array of messages for LangChain, handling tool calls and creating ToolMessage instances.
*
* @param {Array<Partial<TMessage>>} payload - The array of messages to format.
* @returns {Array<(HumanMessage|AIMessage|SystemMessage|ToolMessage)>} - The array of formatted LangChain messages, including ToolMessages for tool calls.
*/
const formatAgentMessages = (payload) => {
const messages = [];
for (const message of payload) {
if (message.role !== 'assistant') {
messages.push(formatMessage({ message, langChain: true }));
continue;
}
let currentContent = [];
let lastAIMessage = null;
for (const part of message.content) {
if (part.type === ContentTypes.TEXT && part.tool_call_ids) {
// If there's pending content, add it as an AIMessage
if (currentContent.length > 0) {
messages.push(new AIMessage({ content: currentContent }));
currentContent = [];
}
// Create a new AIMessage with this text and prepare for tool calls
lastAIMessage = new AIMessage({
content: part.text || '',
});
messages.push(lastAIMessage);
} else if (part.type === ContentTypes.TOOL_CALL) {
if (!lastAIMessage) {
throw new Error('Invalid tool call structure: No preceding AIMessage with tool_call_ids');
}
// Note: `tool_calls` list is defined when constructed by `AIMessage` class, and outputs should be excluded from it
const { output, ...tool_call } = part.tool_call;
lastAIMessage.tool_calls.push(tool_call);
// Add the corresponding ToolMessage
messages.push(
new ToolMessage({
tool_call_id: tool_call.id,
name: tool_call.name,
content: output,
}),
);
} else {
currentContent.push(part);
}
}
if (currentContent.length > 0) {
messages.push(new AIMessage({ content: currentContent }));
}
}
return messages;
};
module.exports = {
formatMessage,
formatFromLangChain,
formatAgentMessages,
formatLangChainMessages,
};